If you've written much Streamlit code, you've likely run into a change to one piece of the state (very slowly) re-rendering every plot and table in your app. Is there any way to avoid this?
Pandas DataFrames offer a ton of ways to do the same things and it isn't always obvious to me which option is best. I went ahead and profiled some common situations to compare them.
Many of us take DNA tests or see loved ones suffer from dementia and wonder if there's anything we can do to lower our risk. It turns out that we can delay onset for years.
Just wanted to try out a simple idea for visualizing where I spent my time. Each marker is centered at a location I spent at least 24 hours straight, and the marker size increases with the amount of time spent there.
My son asked about a seemingly simple dice game and I didn't know how to
answer immediately. The question is:
Player 1 rolls a 6-sided die. Player 2 rolls a 6-sided die. If player 2
rolls the same as player 1, he rolls again. If he again rolls the same, he
loses. How often will each player win?
I had trouble finding (working) simple tutorials for running Node.js CRUD apps on AWS using Elastic Beanstalk so I wrote one from scratch and documented it.
Say you run 20 tests before and after a code change meant to speed up the code, but there's a lot of noise in your benchmarks. Some simple statistical tests can help you determine if you actually have an improvement in that noise.